Investigate Low-Cost Hospital Efficiency Measures to Improve Patient Care
An initiative of the Department of Mechanical and Industrial Engineering at the University of Toronto, the Centre for Research in Healthcare Engineering (CRHE) focuses on the application of Industrial/Systems Engineering techniques in relation to demand and capacity modeling and resource allocation issues in the health care industry.
Visual8 and CRHE have successfully partnered together on several health care simulation projects. As a leader in the use of computer modeling and simulation, Visual8’s valuable support has contributed directly to CRHE’s success.
CRHE was engaged by an independent policy think tank that focuses on building capability for
improvement in the delivery of healthcare in Ontario. This group has been actively engaged with the
Ministry of Health and Long-Term Care to help make effective policy decisions.
The goal of this engagement was to develop a learning tool that could demonstrate the benefit of a set
of widely acknowledged yet often misunderstood hospital efficiency initiatives. It was determined that
a visual model of the impact of these initiatives would be the most effective way to communicate the
need for hospitals to adopt the changes in question.
The model would allow hospital administrators to investigate the impact of a variety of operational strategies such as:
- What are the effects of pooling capacity within the inpatient units in the hospital?
- How will adding additional capacity impact each stage of the healthcare system?
- Will attempting to align resource capacity more closely with demand reduce wait times?
The overarching goal was to develop a tool to aid in making knowledgeable and effective decisions to improve patient care through low-cost hospital efficiency measures.
A generic simulation of a hospital was created in SIMUL8 with an Emergency Room, ICU, and Medical
Wards. At a higher level capacity for Homecare, Rehabilitation and Long-Term Care were modeled.
The resulting simulation was integrated with an Excel interface to allow the user to investigate the
impact of seven different operating strategies by demonstrating results through a generic model of a
The operating strategies demonstrated by the Healthcare Initiative Learning Interface included:
- Segmenting Capacity in ED
- Managing Waitlists
- Segmenting Capacity on Inpatient Units
- Understanding the Impact of Length of Stay Variation
- Matching Capacity to Demand
- Discharging on Weekends
- Altering Capacity and Routing
This tool allows the user to examine the impact of a set of widely acknowledged yet often
misunderstood hospital efficiency initiatives. These include segmenting capacity in the ED, managing
waitlists, and matching resource capacity to demand. The results of the simulation help underline the
impact that these initiatives can have on wait times.
The tool was structured in such a way to allow easy distribution to interested parties. The modeled
scenarios contained common inputs that the user could modify to interactively learn about how hospital
systems typically react to these types of changes. In this way the model demonstrates some effective
decisions that can improve patient care through low-cost operational strategies.